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- jump Markov model 跳跃马尔可夫模型
- This paper presents a discrete Markov model for analyzing the PFD(avg). 该文提出了一种采用离散Markov模型定量计算PFD(avg)的有效方法。
- CONCLUSIONS:Markov model should be applied in drug market extensively. 结论:马尔科夫模型应在药品经济领域得到推广应用。
- It used Markov modeler to model and forecast spatial series. 使用马尔可夫模型对读请求的空间特征进行建模、预测。
- This paper presents a hybrid model of Continuous Density Hidden Markov Model (CDHMM) and the Multi-Layer Perceptron (MLP). 本文提出了一种由连续隐马尔可夫模型（CDHMM）与多层感知器（MLP）构成的混合模型，并将该模型应用于语音孤立词识别。
- A new synthetic aperture radar (SAR) image filter method is proposed based on hidden Markov model (HMM). 在小波域隐Markov模型(HMM)的基础上提出一种新的合成孔径雷达(SAR)图像的滤波方法。
- So, it is practical to use the sequential clustering and Markov model to forecast the river runoff. 这说明运用马尔可夫模型进行河径流量的丰枯状态预报是有效可行的。
- This paper proposes a novel contour tracking algorithm based on Hidden Markov Model (HMM) and optic flow. 提出了一个新颖的基于隐马尔科夫模型与光流的轮廓线跟踪算法。
- In this thesis, we use both Hidden Markov Model (HMM) and Weight Array Model (WAM) to predict the splice sites. 本文基于隐Markov模型(HMM)和权重阵列模型(WAM)两种方法来预测剪接位点。
- reversible jump Markov chain Monte Carlo (RJMCMC) 可逆跳转马尔可夫链蒙特卡罗
- Transient Analysis of Rewarded Continuous Time Markov Model by Regenerative Randomization with Laplace Transform Inversion. 论文题目:借助拉氏逆变换,运用随机反馈策略对马尔科夫时间连续模型作瞬变性分析。
- Reversible jump Markov Chain Monte Carlo 可逆跳MCMC
- Reversible jump Markov chain Monte Carlo method 可逆跳跃马尔可夫链蒙特卡罗法
- It produces Mongolian translation from the single language material through use of dictionary-based model and Hidden Markov Model. 基于HMM模型的蒙古文生成方法采用词典驱动模型和HMM模型从单语料生成蒙古文译文。
- In this paper, based on DSR we model it as a Markov model, i.e the length of each link in the network is considered as the birth and death process. 本文以DSR协议为基础;把每条链边的长度看作是一个生灭过程;建立了马氏模型.
- Dynamic fault tree is modularized into independent static subtrees and independent dynamic subtrees,then solved by BDD and Markov model separately. 该方法首先将动态故障树进行模块化，得到独立的静态子树和动态子树，再分别用二元决断图法和马尔可夫过程方法求解。
- The strong limit theorem of hidden nonhomogeneous Markov model is studied when the hidden chains are nonhomogeneous Markov chains. 摘要假定隐藏的马尔可夫链为非齐次，研究隐非齐次马尔可夫模型的一些强极限定理。
- The MST in association with the natural history of lung cancer depicted by a three-state Markov model was estimated with a Bayesian approach. 对相应于电脑断层的平均滞留时间，我们用贝氏三阶段马可夫模式分析文献报告来估计。
- As corollaries, several strong limit theorems about occurred frequency of states for hidden nonhomogeneous Markov model are obtained. 作为定理的推论，得到了隐非齐次马尔可夫模型状态出现频率的一类强极限定理。
- Second, we discuss the three base question of Hidden Markov Model, induce two new algorithms, named mend Baum-Welch and mend Viterbi. 其次，本文在研究了隐马尔可夫模型的基础上，对其三个基本问题进行了比较细致的论证，并引入改进Viterbi算法。
